Network information theory promises high gains over simple point-to-point communication techniques, at the cost of higher complexity. However, lack of structured coding schemes limited the practical application of these concepts so far. One of the basic elements of a network code is the binning scheme. Wyner and other researchers proposed various forms of coset codes for efficient binning, yet these schemes were applicable only for lossless source (or noiseless channel) network coding. To extend the algebraic binning approach to lossy source (or noisy channel) network coding, recent work proposed the idea of nested codes, or more specifically, nested parity-check codes for the binary case and nested lattices in the continuous case. These ideas connect network information theory with the rich areas of linear codes and lattice codes, and have strong potential for practical applications. We review these recent developments and explore their tight relation to concepts such as combined shaping and precoding, coding for memories with defects, and digital watermarking. We also propose a few novel applications adhering to a unified approach.

Although people have hidden secrets in plain sight— now called steganography—throughout the ages, the recent growth in computational power and technology has propelled it to the forefront of today’s

Watermarking models a copyright protection mechanism where an original source sequence or "covertext" is modified before distribution to the public in order to embed some extra information. The embedding should be transparent (i.e., the modified data sequence or "stegotext" should be similar to the covertext) and robust (i.e., the extra information should be recoverable even if the stegotext is modified further, possibly by a malicious "attacker"). We compute the coding capacity of the watermarking game for a Gaussian covertext and squared-error distortions. Both the public version of the game (covertext known to neither attacker nor decoder) and the private version of the game (covertext unknown to attacker but known to decoder) are treated. While the capacity of the former cannot, of course, exceed the capacity of the latter, we show that the two are, in fact, identical. These capacities depend critically on whether the distortion constraints are required to be met in expectation or with probability one. In the former case the coding capacity is zero, whereas in the latter it coincides with the value of related zero-sum dynamic mutual informations games of complete and perfect information. # Parts of this work were presented at the 2000 Conference on Information Sciences and Systems (CISS '00), Princeton University, Princeton, NJ, March 15--17, 2000, and at the 2000 IEEE International Symposium on Information Theory (ISIT '00), Sorrento, Italy, June 25--30, 2000.

Abstract—A novel reversible data hiding algorithm, which can recover the original image without any distortion from the marked image after the hidden data have been extracted, is presented in this paper. This algorithm utilizes the zero or the minimum points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. It can embed more data than many of the existing reversible data hiding algorithms. It is proved analytically and shown experimentally that the peak signal-to-noise ratio (PSNR) of the marked image generated by this method versus the original image is guaranteed to be above 48 dB. This lower bound of PSNR is much higher than that of all reversible data hiding techniques reported in the literature. The computational complexity of our proposed technique is low and the execution time is short. The algorithm has been successfully applied to a wide range of images, including commonly used images, medical images, texture images, aerial images and all of the 1096 images in CorelDraw database. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed algorithm. Index Terms—Histogram modification, reversible (lossless) data hiding, watermarking. I.

Research on information embedding and particularly information hiding techniques has received considerable attention within the last years due to its potential application in multimedia security. Digital watermarking, which is an information hiding technique where the embedded information is robust against malicious or accidental attacks, might offer new possibilities to enforce the copyrights of multimedia data. In this article, the specific case of information embedding into independent identically distributed (IID) data and attacks by additive white Gaussian noise (AWGN) is considered. The original data is not available to the decoder. For Gaussian data, Costa proposed already in 1983 a scheme that theoretically achieves the capacity of this communication scenario. However, Costa's scheme is not practical. Thus, several research groups have proposed suboptimal practical communication schemes based on Costa's idea. The goal of this artical is to give a complete performance analysis of the scalar Costa scheme (SCS) which is a suboptimal technique using scalar embedding and reception functions. Information theoretic bounds and simulation results with state-of-the-art coding techniques are compared. Further, reception after amplitude scaling attacks and the invertibility of SCS embedding are investigated. Keywords Information embedding, communication with side-information, blind digital watermarking, scalar Costa scheme I.

Digital fingerprinting is a technique for identifying users who might try to use multimedia content for unintended purposes, such as redistribution. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cost-e#ective attack against such digital fingerprints is collusion, where several di#erently marked copies of the same content are combined to disrupt the underlying fingerprints. In this paper, we investigate the problem of designing fingerprints that can withstand collusion and allow for the identification of colluders. We begin by introducing the collusion problem for additive embedding. We then study the e#ect that averaging collusion has upon orthogonal modulation. We introduce an e#cient detection algorithm for identifying the fingerprints associated with K colluders that requires log(n/K)) correlations for a group of n users. We next develop a fingerprinting scheme based upon code modulation that does not require as many basis signals as orthogonal modulation. We propose a new class of codes, called anti-collusion codes (ACC), which have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we can therefore identify groups of K or fewer colluders. We present a construction of binary-valued ACC under the logical AND operation that uses the theory of combinatorial designs and is suitable for both the on-o# keying and antipodal form of binary code modulation. In order to accommodate n users, our code construction requires only # n) orthogonal signals for a given number of colluders. We introduce four di#erent detection strategies that can be used with our ACC for identifying a suspect set of colluders. We demonstrate th...

Steganography is used to hide the occurrence of communication. Recent suggestions in US newspapers indicate that terrorists use steganography to communicate in secret with their accomplices. In particular, images on the Internet were mentioned as the communication medium. While the newspaper articles sounded very dire, none substantiated these rumors. To determine whether there is steganographic content on the Internet, this paper presents a detection framework that includes tools to retrieve images from the world wide web and automatically detect whether they might contain steganographic content. To ascertain that hidden messages exist in images, the detection framework includes a distributed computing framework for launching dictionary attacks hosted on a cluster of loosely coupled workstations. We have analyzed two million images downloaded from eBay auctions and one million images obtained from a USENET archive but have not been able to find a single hidden message.

Abstract—Aspects of the duality between the information-embedding problem and the Wyner–Ziv problem of source coding with side information at the decoder are developed and used to establish a spectrum new results on these and related problems, with implications for a number of important applications. The singleletter characterization of the information-embedding problem is developed and related to the corresponding characterization of the Wyner–Ziv problem, both of which correspond to optimization of a common mutual information difference. Dual variables and dual Markov conditions are identified, along with the dual role of noise and distortion in the two problems. For a Gaussian context with quadratic distortion metric, a geometric interpretation of the duality is developed. From such insights, we develop a capacity-achieving information-embedding system based on nested lattices. We show the resulting encoder–decoder

A considerable amount of attention has been lately payed to a number of data hiding methods based in quantization, seeking to achieve in practice the results predicted by Costa for a channel with side information at the encoder. With the objective of filling a gap in the literature, this paper supplies a fair comparison between significant representatives of both this family of methods and the former spread-spectrum approaches that make use of near-optimal ML decoding; the comparison is based on measuring their probabilities of decoding error in the presence of channel distortions. Accurate analytical expressions and tight bounds for the probability of decoding error are given and validated by means of Monte Carlo simulations. For Dithered Modulation (DM) a novel technique that allows to obtain tighter bounds to the probability of error is presented. Within the new framework, the strong points and weaknesses of both methods are distinctly displayed. This comparative study allows us to propose a new technique named "Quantized Projection" (QP), which by adequately combining elements of those previous approaches, produces gains in performance.

Electronic watermarking can be traced back as far as 1954. The last 10 years has seen considerable interest in digital watermarking, due in large part to concerns about illegal piracy of copyrighted content. In this paper, we consider the following questions: Is the interest warranted? What are the commercial applications of the technology? What scientific progress has been made in the last 10 years? What are the most exciting areas for research? And where might the next 10 years take us? In our opinion, the interest in watermarking is appropriate. However, we expect that copyright applications will be overshadowed by applications such as broadcast monitoring, authentication, and tracking content distributed within corporations. We further see a variety of applications emerging that add value to media, such as annotation and linking content to the Web. These latter applications may turn out to be the most compelling. Considerable progress has been made toward enabling these applications – perceptual modelling, security threats and countermeasures, and the development of a bag of tricks for efficient implementations. Further progress is needed in methods for handling geometric and temporal distortions. We expect other exciting developments to arise from research in informed watermarking.